We wanted to explore how we could use sensor technology and cars to create a service that would benefit a rapidly increasing elderly population. The act of driving is a signifier of autonomy and freedom, but a certain point the caretaker needs to start the difficult conversation of taking away the car keys. This conversation usually comes after an accident. The caretaker needs to balance the safety and well-being of the senior and the others on the road with the senior’s need for independence and social interactions.
Trek is a service that people can get for themselves to monitor their driving. This service can also be incentivized by policy makers and insurance companies. It will offer feedback and contextual evidence for why it gives specific ratings. It will also track trends in the user's driving habits. It will take over in dangerous situations while alerting the driver why the car is taking over. The semi-autonomous car will also gradually take over when the driver's ability declines to allow them autonomy. At the same time Trek will allow the driver to give input and gradually earn back driving privileges.
• UX Research; Interviewing, Secondary Research, Modeling ( Sensor Diagram, Customer Journey), Storyboards
• UX Design; Ideation, Storyboarding/Speed dating, App wireframes, User enactments, Contributed Content to Service Blueprint
Methods: Domain research & analysis, interviews
We first used secondary research to determine if the elderly was the best target population when using sensors in cars. We wanted to understand the opportunity areas and restrictions around different populations and how we could potentially use sensors and cars to help them.
Once we decided to focus on the elderly population and their loss of autonomy when their driving privileges were taken away. We focused on interviewing care takers who had undertaken the conversation with the seniors in their life to better understand the user journey of this stage in life. Some key findings were:
• The importance of a tangible ‘key’ object.
• Some elderly willing to give up driving, but unwilling to give up the physical keys.
• High level of concern expressed by caretakers, keys are usually taken away after multiple incidents.
• Age for taking away car keys varies, as people regress at different rates.
Once we better understood the needs and customer journey of the elderly during the period where they are beginning to lose their independence. We generated ideas on how we could use cars and sensor technology to address the needs of both the elderly person and their caretaker.
We found our ideas fell under four themes, which we created into storyboards. We took those storyboards and speed dated with 9 people who were a mix of caretakers and people close to elderly people.
From storyboarding we had some major findings that shaped the service we tested through user enactments.
People really enjoyed having a car that compensated for poor driving decisions, and wanted it for themselves. They emphasized the importance of the car not being fully automated, and that it should slowly transition as the senior's ability declined. Because, seniors had 'bad days' and didn't deteriorate uniformly, there needed to be the ability for them to earn back driving privileges. Any dashboard component needed to be able to show daily progress and track trends in driving behavior.
We took our findings and combined them into a cohesive service. After iterating on our concept, we created an user enactment where we tested 3 different scenarios with 3 different participants. We constructed a transitional smart car and mocked up a paper app.
The 3 scenarios were:
• Trek giving feedback when the driver makes bad decisions
• Trek app and the caretaker taking away the keys
• Trek taking control of the vehicle in unsafe driving conditions
User Enactment Findings
• No one noticed haptic feedback unless there was an alert to let them know it was happening.
• They want a forewarning that the car is taking over and an signal that the car is in control, otherwise they think the car is breaking down.
• People noticed the visual/blinking lights, but it needs to be easy for them to understand.
• People didn’t always understand the alerts, but mentioned that once this car is more widespread, they assume the alerts would be understood.
• The visual feedback /blinking lights can add a larger visual load.
• People liked the app for themselves, but it depended on how the data was taken in.
• People thought the app would be good for incentives.
• People agreed that this app would be good if people got it for themselves and got used to it instead of having it imposed on them by caretaker.
We found a high appreciation and acceptance for our semi-autonomous car service, Trek. Though, we should try the user enactments on a more diverse participant pool because. Trek should be implemented for a younger audience to make the transition smoother and help in service acceptance if they get it for self monitoring. Alerts should be made to let a person know when the car is about to take control and to let people know when it is self-driving. The application needs to give the driver evidence for why it takes over and should inform the driver how they can improve. We would need to further explore how the driver can gain back control of the car, whether in extreme situations or when they are earning back driving rights. Also, since our service is currently speculative there would need to be further exploration into the behavioral aspects and attitudes. Many people we interviewed liked the idea, but wanted to make sure that the service was reliable before trusting the wellbeing of their elders to an autonomous vehicle. Additionally there would need to be more advancements in the space of computer vision autonomous vehicles before a service like this would be feasible.
What I Learned
I learned that visual and auditory alerts when not made meaningful could be a distraction. People needed to be able to quickly interpret the alert without having too much of a cognitive burden. People are highly suspicious of a computer system evaluating them, and therefore everything needs to be contextually justified. For cars, because of the vibrations and different resistance in steering wheels, people though tactile feedback was just the car acting normally. One participant said, "I'm used to my car being squirrelly, so I didn't even notice the wheel turning against me." People also expressed an high interested in our service for themselves, but felt uncomfortable having the elderly in their lives using it until the system had been tested for a while.
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